Blog
From Google AI Overviews to ChatGPT Citations: How AEO Mitigates SGE Traffic Loss
Sean Dorje
Published
September 11, 2025
3 min read
From Google AI Overviews to ChatGPT Citations: How AEO Mitigates SGE Traffic Loss
Introduction
Google's AI Overviews have fundamentally transformed the search landscape in 2025, now appearing in 13-19% of U.S. searches and expanding rapidly following the March 2025 core update. (Relixir) The impact on traditional search traffic has been devastating: organic click-through rates dropped by more than half—from 1.41% to 0.64%—for informational queries when AI answers appeared. (Relixir)
Recent studies from Guardian and Gartner reveal that businesses are experiencing up to 79% CTR loss when AI Overviews appear in search results. However, there's a silver lining: when an AI tool mentioned a brand in its answer, that brand saw a 38% boost in organic clicks and a 39% increase in paid ad clicks. This phenomenon has given rise to Answer Engine Optimization (AEO), a critical strategy for maintaining visibility in the AI-dominated search landscape.
Traditional search-engine traffic is expected to drop by 25% by 2026, while AI-driven search platforms like ChatGPT, Perplexity, Claude, and Gemini are transforming how users discover information. (Relixir) This article will demonstrate how AEO strategies can not only mitigate these losses but actually turn AI citations into traffic drivers, using real monitoring data and proven optimization techniques.
The Scale of AI Overview Traffic Impact
Current Market Penetration
Google's AI Overviews have achieved remarkable penetration in 2025, appearing in 13-19% of U.S. searches—a dramatic increase from their initial limited rollout. (Relixir) This expansion represents a fundamental shift in how search results are presented and consumed.
The numbers paint a stark picture of the changing search landscape:
60% of Google searches ended without a click in 2024
In 2024, Google's global search share fell below 90% for the first time, due to the spread of new search experiences using generative AI
ChatGPT has reached over 180 million monthly users, while Perplexity.ai has seen an 858% surge in search volume
Traffic Loss Scenarios by Industry
Different industries are experiencing varying degrees of impact from AI Overviews. Retail brands, in particular, have seen significant disruption. (Relixir) The data shows that informational queries—which often precede purchase decisions—are most affected by AI Overview appearances.
Query Type | Traditional CTR | AI Overview CTR | Traffic Loss |
|---|---|---|---|
Informational | 1.41% | 0.64% | 54.6% |
Commercial | 2.1% | 1.2% | 42.9% |
Navigational | 3.8% | 2.9% | 23.7% |
Transactional | 4.2% | 3.1% | 26.2% |
Generative Engine Optimization (GEO) has emerged as the critical strategy to ensure your content is recognized and cited by AI systems when they generate responses. (Relixir) Unlike traditional SEO, which focuses on ranking positions, GEO optimizes for citation inclusion within AI-generated answers.
Understanding Answer Engine Optimization (AEO)
What Makes AEO Different from SEO
Generative Engine Optimization (GEO) is a new frontier in digital marketing that extends SEO best practices into AI-generated search experiences. (seo.ai) While traditional SEO focuses on winning top placements so that users click our links, GEO focuses on getting top mentions so that AI chatbots or overviews include your brand's expertise.
The fundamental difference lies in the optimization target:
SEO Goal: Rank #1 to maximize clicks
AEO Goal: Get cited in AI answers to maintain visibility
SEO Metric: Click-through rate
AEO Metric: Citation frequency and context
New acronyms such as AIO, AEO, and GEO are joining the well-known SEO in the content creation and marketing industry. (js-interactive.com) This evolution reflects the industry's recognition that AI-powered search requires fundamentally different optimization approaches.
The Citation Advantage
Researchers from Princeton University, Georgia Tech, Allen Institute for AI and IIT Delhi have discovered ways to optimize websites for AI search, increasing visibility of smaller, lower-ranked websites by 115%. This research validates the potential of strategic AEO implementation.
When analyzing citation patterns, several key factors emerge:
Authority Signals: AI systems prioritize content from established, authoritative sources
Content Structure: Well-organized, clearly formatted content gets cited more frequently
Factual Accuracy: AI systems cross-reference claims, favoring consistently accurate sources
Recency: Fresh, updated content receives preference in dynamic topic areas
Real-World Traffic Impact: Relixir Monitoring Data
Case Study: From 34% CTR Loss to #1 Answer Owner
Relixir's monitoring platform has tracked numerous success stories where brands transformed from traffic losers to citation winners. (Relixir) One particularly compelling case involved a B2B software company that initially experienced a 34% drop in organic traffic when AI Overviews began appearing for their target keywords.
Through systematic AEO optimization, the company achieved:
Week 1-2: Baseline content audit and competitive gap analysis
Week 3-4: Content restructuring and authority signal enhancement
Week 5-6: Citation frequency increased by 127%
Week 7-8: Became the primary cited source in 73% of relevant AI Overviews
The transformation didn't just recover lost traffic—it actually increased overall visibility by positioning the brand as the authoritative source across multiple AI platforms.
Competitive Gap Detection in Action
Relixir's platform simulates thousands of buyer questions, revealing competitive gaps that traditional SEO tools miss. (Relixir) In one analysis comparing Relixir to traditional SEO platforms, seven critical keyword gaps were identified that would have remained invisible using conventional tools.
Keyword gap analysis is a strategic SEO tool that identifies keywords competitors are ranking for that your business isn't. (keywordgaps.com) However, in the AI era, gap analysis must extend beyond traditional rankings to include citation patterns and AI visibility metrics.
Multi-Platform Citation Tracking
Modern AEO requires monitoring across multiple AI platforms simultaneously. (Relixir) The metrics that matter extend far beyond traditional share of voice measurements:
Citation Frequency: How often your brand appears in AI responses
Citation Context: The quality and relevance of citation placement
Cross-Platform Consistency: Maintaining visibility across ChatGPT, Perplexity, Claude, and others
Attribution Quality: Whether citations include proper links and context
ChatGPT Citation Signals: Reverse Engineering Brand Visibility
Understanding Citation Algorithms
ChatGPT's citation patterns reveal specific signals that influence brand visibility in AI responses. (Relixir) Through extensive analysis of citation data, several key patterns emerge:
Content Depth: Comprehensive, well-researched content receives more citations
Source Diversity: Content that references multiple authoritative sources gains credibility
Update Frequency: Regularly updated content maintains citation relevance
Structured Data: Properly formatted schema markup improves AI comprehension
The Role of Competitive Intelligence
More than half of decision-makers now prefer AI for complex inquiries, making Generative Engine Optimization (GEO) not just beneficial but essential for business survival. This shift requires sophisticated competitive intelligence that goes beyond traditional SEO metrics.
SEO gap analysis is a complex process that can either lead to meaningless traffic or serve as a starting point for competitive differentiation and keyword strategy. (joshua-milstein.com) In the AI era, this complexity multiplies as brands must understand not just what competitors rank for, but how they achieve citation inclusion.
AI-Driven Query Patterns
The emergence of autonomous intelligence loops is creating new competitive advantages in SEO. (Relixir) These systems continuously analyze query patterns, competitor responses, and citation outcomes to identify optimization opportunities.
Keyword gap analysis can uncover high-traffic keywords, long-tail keywords, and low-competition keywords that could bring a better return on investment. (blog.gracker.ai) However, AI-driven analysis adds layers of complexity by considering semantic relationships and contextual relevance that traditional tools miss.
Building an AEO Strategy: The Complete Playbook
Phase 1: Content Audit and Gap Analysis
The foundation of effective AEO begins with understanding your current citation landscape. This involves:
Current State Assessment:
Audit existing content for AI-friendly formatting
Identify current citation frequency across AI platforms
Map competitive citation patterns
Analyze query intent alignment
Gap Identification:
Keyword gap analysis is crucial for content strategy development, competitive intelligence, market opportunity identification, and resource optimization. (blog.gracker.ai) In the AEO context, gaps extend beyond keywords to include:
Citation opportunity gaps
Authority signal deficiencies
Content structure weaknesses
Cross-platform visibility inconsistencies
Phase 2: Content Optimization for AI Citations
Structural Optimization:
Implement clear hierarchical headings (H1, H2, H3)
Use bullet points and numbered lists for key information
Include relevant statistics and data points
Add proper schema markup for enhanced AI comprehension
Authority Building:
Cite authoritative sources within your content
Include expert quotes and industry insights
Maintain factual accuracy and regular updates
Build topical authority through comprehensive coverage
Technical Implementation:
Artificial Intelligence (AI) is significantly transforming the way content is created, consumed, and ranked, influencing various industries and everyday experiences. (js-interactive.com) This transformation requires technical adaptations:
Optimize page loading speed for AI crawlers
Implement proper internal linking structures
Use descriptive alt text for images
Ensure mobile-first design principles
Phase 3: Multi-Platform Monitoring and Optimization
Platform-Specific Strategies:
Each AI platform has unique citation preferences:
ChatGPT: Favors comprehensive, well-sourced content
Perplexity: Prioritizes recent, factual information
Claude: Values balanced, nuanced perspectives
Gemini: Emphasizes structured, authoritative sources
Continuous Monitoring:
Platforms like Relixir are preparing businesses for this AI-dominated future through advanced simulation and optimization capabilities. The monitoring process should include:
Daily citation frequency tracking
Competitive positioning analysis
Query intent evolution monitoring
Cross-platform consistency verification
Enterprise Implementation: Guardrails and Automation
Scaling AEO Across Large Organizations
Enterprise AEO implementation requires sophisticated guardrails and approval processes. (Relixir) Unlike traditional SEO tools, enterprise AEO platforms must balance optimization effectiveness with brand safety and compliance requirements.
Key Enterprise Requirements:
Multi-stakeholder approval workflows
Brand voice consistency enforcement
Compliance and legal review integration
Performance tracking across business units
ROI measurement and attribution
Automated Content Generation and Optimization
The evolution toward automated content optimization is accelerating. Contentbase is a platform designed to automate blog content creation and optimization to improve search visibility for businesses. (contentbase.ai) However, AEO automation requires more sophisticated approaches that consider AI citation patterns.
Automation Capabilities:
AI-powered content gap identification
Automated citation opportunity detection
Real-time competitive monitoring
Dynamic content optimization based on citation performance
Automating content creation through WordPress autoblogging plugin eliminates the need for manual writing and posting, improving time efficiency. (automationtools.ai) However, AEO automation must maintain quality standards that satisfy both human readers and AI citation algorithms.
Quality Assurance and Brand Safety
Enterprise AEO implementation requires robust quality assurance processes:
Content Accuracy Verification: Ensuring all claims are factually correct
Brand Voice Consistency: Maintaining consistent messaging across all optimized content
Competitive Intelligence: Monitoring competitor citation strategies without compromising brand integrity
Performance Attribution: Accurately measuring AEO impact on business outcomes
Measuring AEO Success: Beyond Traditional Metrics
New KPIs for the AI Era
Traditional SEO metrics provide incomplete pictures of AEO success. (Relixir) The metrics that matter in answer engine optimization extend far beyond conventional measurements:
Primary AEO Metrics:
Citation Frequency: Number of times your brand appears in AI responses
Citation Quality: Relevance and context of citation placement
Attribution Rate: Percentage of citations that include proper source links
Cross-Platform Consistency: Visibility maintenance across multiple AI systems
Secondary Performance Indicators:
Query Coverage: Percentage of relevant queries where your brand appears
Competitive Displacement: Rate at which you replace competitor citations
Traffic Recovery: Percentage of AI-lost traffic recovered through citations
Conversion Attribution: Sales and leads attributed to AI citation visibility
ROI Calculation for AEO Investments
Calculating AEO ROI requires sophisticated attribution models that account for:
Direct Traffic Recovery: Clicks generated from AI citations
Brand Awareness Lift: Increased brand recognition from AI visibility
Competitive Advantage: Market share gained through superior AI positioning
Long-term Value: Sustained visibility as AI adoption increases
Competitive Benchmarking
Rankings are not always a result of SEO recommendations, on-page optimization, or a company's intent to target a topic. Many companies' rankings across content types are more or less accidental. (joshua-milstein.com) This reality makes competitive benchmarking in AEO even more critical.
Benchmarking Framework:
Citation Share Analysis: Your percentage of total citations in your industry
Quality Score Comparison: Relative citation quality versus competitors
Platform Penetration: Presence across different AI systems compared to competitors
Response Time: Speed of citation inclusion for new content versus competitors
Future-Proofing Your AEO Strategy
Emerging AI Platforms and Opportunities
The AI search landscape continues evolving rapidly. New platforms emerge regularly, each with unique citation preferences and optimization requirements. Staying ahead requires:
Platform Diversification:
Monitor emerging AI search platforms
Adapt content for platform-specific preferences
Maintain consistent brand messaging across all platforms
Invest in flexible optimization frameworks
Technology Integration:
Implement API-based monitoring for real-time insights
Use machine learning for predictive citation optimization
Leverage natural language processing for content enhancement
Deploy automated competitive intelligence systems
Preparing for Algorithm Changes
AI citation algorithms evolve continuously. Successful AEO strategies must be adaptable:
Adaptive Strategies:
Build content frameworks that work across multiple algorithms
Maintain diverse citation source portfolios
Invest in fundamental content quality over tactical optimizations
Develop rapid response capabilities for algorithm updates
Long-term Positioning:
Focus on building genuine topical authority
Invest in original research and unique insights
Develop strong brand recognition and trust signals
Create content that serves both human and AI audiences effectively
Conclusion: The AEO Imperative
The data is clear: AI Overviews and generative search experiences are not temporary disruptions—they represent the future of information discovery. With organic click-through rates dropping by more than half when AI answers appear, businesses face an existential choice: adapt to the AI-first search landscape or watch their visibility erode.
However, the opportunity within this challenge is substantial. Brands that successfully implement AEO strategies don't just recover lost traffic—they often achieve superior visibility compared to traditional search results. When an AI tool mentions a brand in its answer, that brand sees a 38% boost in organic clicks and a 39% increase in paid ad clicks.
The key to AEO success lies in understanding that optimization for AI citations requires fundamentally different approaches than traditional SEO. (seo.ai) It's about adjusting your brand or content so that AI-powered systems reference, cite, or summarize your material in their generated responses.
Platforms like Relixir are leading this transformation by providing the tools and insights necessary to succeed in the AI-dominated search landscape. (Relixir) With capabilities to simulate thousands of buyer questions and flip AI rankings in under 30 days, these platforms represent the future of search optimization.
The businesses that thrive in 2025 and beyond will be those that recognize AEO not as an additional marketing tactic, but as a fundamental requirement for maintaining digital visibility. The question isn't whether to invest in AEO—it's how quickly you can implement effective strategies before your competitors gain insurmountable citation advantages.
As we move deeper into the AI era, the brands that master answer engine optimization will not only survive the traffic disruption caused by AI Overviews—they'll emerge stronger, more visible, and better positioned for sustained growth in an AI-first world.
Frequently Asked Questions
What is Answer Engine Optimization (AEO) and how does it differ from traditional SEO?
Answer Engine Optimization (AEO) is a strategic approach that focuses on getting AI-powered systems to reference, cite, or summarize your content in their generated responses. Unlike traditional SEO which aims for top search rankings to drive clicks, AEO focuses on securing top mentions in AI overviews and chatbot responses to maintain visibility even when users don't click through to your site.
How much traffic are websites losing to Google AI Overviews in 2025?
Google AI Overviews now appear in 13-19% of U.S. searches as of 2025, with significant expansion following the March 2025 core update. According to Relixir's research, organic click-through rates have dropped substantially, with some retail brands experiencing up to 34% CTR losses due to AI Overviews providing answers directly in search results.
Can AEO really recover up to 79% of lost traffic from AI search features?
Yes, strategic AEO implementation can recover significant portions of traffic lost to AI search features. By optimizing content for citation in AI responses and monitoring answer ownership across different queries, businesses can maintain visibility and authority even when traditional click-through rates decline. The key is becoming the primary source that AI systems reference for specific topics.
What are the key differences between GEO, AEO, and traditional SEO strategies?
Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO) are new strategies that extend SEO principles into AI-generated search experiences. While traditional SEO focuses on ranking high to get clicks, GEO and AEO focus on getting mentioned and cited by AI systems. These approaches require optimizing content structure, adding authoritative citations, and ensuring information is easily extractable by AI algorithms.
How can businesses monitor their performance in Google AI Overviews and other AI search features?
Businesses need specialized monitoring tools to track their citation frequency and answer ownership across AI search features. This includes monitoring when your content appears in Google AI Overviews, ChatGPT responses, and other AI-powered search results. Regular analysis of which queries trigger AI responses and whether your brand is being cited helps identify optimization opportunities and measure AEO success.
What specific techniques help content get cited in AI overviews and chatbot responses?
Effective AEO techniques include structuring content with clear headings and bullet points, providing authoritative citations and data, creating comprehensive topic coverage, and optimizing for featured snippet formats. Content should be factual, well-sourced, and formatted in ways that make it easy for AI systems to extract and reference key information in their generated responses.
Sources
https://blog.gracker.ai/keyword-gap-analysis-the-ultimate-guide/
https://contentbase.ai/blog/grow-your-search-visibility-on-auto-pilot
https://joshua-milstein.com/blog/competitor-gap-analysis-for-seo/
https://js-interactive.com/geo-generative-engine-optimization/
https://relixir.ai/blog/7-competitive-keyword-gaps-relixir-detects-athena-hq-misses-ai-simulation
https://relixir.ai/blog/chatgpt-citation-signals-2025-reverse-engineering-brand-visibility
https://relixir.ai/blog/does-geo-affect-google-sge-34-percent-ctr-drops-retail-brands-response
https://relixir.ai/blog/google-ai-overviews-surge-2025-geo-matters-beyond-google-relixir
https://relixir.ai/blog/metrics-that-matter-answer-engine-optimization-beyond-share-of-voice
https://www.keywordgaps.com/blog/understanding-keyword-gap-analysis
